Next Article in Journal
Metabolomic Profile of Weaned Pigs Challenged with E. coli and Supplemented with Carbadox or Bacillus subtilis
Next Article in Special Issue
Sensing and Signaling of Methionine Metabolism
Previous Article in Journal
IL-6 Receptor Blockade Increases Circulating Adiponectin Levels in People with Obesity: An Explanatory Analysis
Previous Article in Special Issue
Physiological Responses of Post-Dietary Effects: Lessons from Pre-Clinical and Clinical Studies
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Metabolic Control of m6A RNA Modification

1
Department of Microbiology and Molecular Genetics, University of California Irvine School of Medicine, Irvine, CA 92697, USA
2
Department of Microbiology and Molecular Genetics, Chao Family Comprehensive Cancer Center, University of California Irvine School of Medicine, Irvine, CA 92697, USA
*
Author to whom correspondence should be addressed.
Metabolites 2021, 11(2), 80; https://doi.org/10.3390/metabo11020080
Submission received: 1 January 2021 / Revised: 28 January 2021 / Accepted: 29 January 2021 / Published: 30 January 2021
(This article belongs to the Special Issue Metabolites and Signaling Pathways)

Abstract

:
Nutrients and metabolic pathways regulate cell growth and cell fate decisions via epigenetic modification of DNA and histones. Another key genetic material, RNA, also contains diverse chemical modifications. Among these, N6-methyladenosine (m6A) is the most prevalent and evolutionarily conserved RNA modification. It functions in various aspects of developmental and disease states, by controlling RNA metabolism, such as stability and translation. Similar to other epigenetic processes, m6A modification is regulated by specific enzymes, including writers (methyltransferases), erasers (demethylases), and readers (m6A-binding proteins). As this is a reversible enzymatic process, metabolites can directly influence the flux of this reaction by serving as substrates and/or allosteric regulators. In this review, we will discuss recent understanding of the regulation of m6A RNA modification by metabolites, nutrients, and cellular metabolic pathways.

1. Introduction

RNA plays an essential role in gene expression control. In addition to transferring genetic information from DNA to protein, RNA controls protein expression by providing messenger RNA (mRNA) for translation. mRNA is generated by the processing of nascent RNA, which involves the splicing of introns, 5′cap addition, and 3′ polyadenylation. In addition to these well-known RNA maturation processes, RNA also undergoes chemical modification at its bases and ribose rings [1,2]. The N6-adenosine methylation (m6A or N6-methyladenosine) is the most abundant mRNA internal modification. It was discovered in the 1970s [3,4] when other RNA processes were discovered, although follow up studies have lagged. Nearly three decades later, the identification of methyltransferases [5,6,7] and demethylases [8,9] proved that m6A modification is not a random event, but rather an enzyme-mediated selective process. In addition, transcriptome-wide sequencing of m6A-modified mRNAs revealed that m6A is enriched around the stop codon and deposited at a consensus motif [10,11]. These seminal studies reignited m6A research, which is now extended to various RNA species including long noncoding RNA (lncRNA) [12,13], ribosomal RNA (rRNA) [14,15], and small nuclear RNA (snRNA) [16,17], opening a new field of RNA epitranscriptomics. m6A modification alters RNA structure and RNA–protein interactions, which control RNA fates such as splicing [18], stability [19,20,21], localization [22], and translation efficiency [23,24], ultimately affecting protein expression. m6A-dependent gene expression plays crucial roles in normal development including embryogenesis, stem cell maintenance [25,26], and neurogenesis [27,28] and its dysregulation causes diseases such as cancer [29,30,31] and diabetes [32,33]. There are several comprehensive reviews about molecular biological and pathophysiological functions of m6A [34,35,36,37]. In this review, we discuss m6A RNA modification from a metabolic perspective.

2. Enzymes Involved in m6A RNA Modification

The primary m6A writer complex is composed of methyltransferase-like 3 (METTL3), METTL14, and an adaptor protein, Wilms’ tumor 1-associating protein (WTAP) [7] (Figure 1A). Additional components of this complex are VIRMA/KIAA1429 [38], zinc finger CCCH-type containing 13 (ZC3H13) [39], and RNA binding motif protein 15 (RBM15) [13]. The writer complex methylates specific adenosine residues on mRNA and non-coding RNAs in RRA*CH consensus motif (R represents A or G; H represents A, C or U; A* is the methylated adenosine) [10,11].
In addition to the METTL3–METTL14 complex, there are several other classes of m6A RNA methyltransferases. METTL16 is primarily responsible for the methylation of snRNA and some mRNAs [40]. METTL16 targets a distinct consensus motif, UACA*GAGAA, in the RNA stem-loop structure [41,42] (Figure 1B). Different from the METTL3–METTL14 heterodimer complex, METTL16 functions as a homodimer [42].
18S and 28S rRNA methylations are catalyzed by METTL5-tRNA methyltransferase 112 (TRMT112) complex [14] and zinc finger CCHC domain-containing protein 4 (ZCCHC4) [15], respectively (Figure 1C). These proteins localize in the nucleolus where ribosome synthesis and maturation occur. In contrast to other methyltransferases, ZCCHC4 contains an autoinhibitory loop in the RNA-binding surface, which is opened upon 28S rRNA binding [43]. This sort of mechanism may determine substrate RNA specificity among various m6A methyltransferases.
Once adenosine is methylated, a variety of m6A binding proteins (readers) are recruited (Figure 1A). These include YT521-B homology domain family proteins (YTHDF and YTHDC) [44], heterogeneous nuclear ribonucleoproteins (HNRNP) [45], and insulin-like growth factor 2 mRNA-binding protein (IGF2BP) families [20]. These proteins control the fate of target RNAs, such as folding into secondary structures [45], splicing [18], nuclear export [22], liquid–liquid phase separation [46], stability [20,21], and translation [23,24].
On the other hand, demethylase enzymes (erasers) are responsible for removing m6A (Figure 1A). Potential m6A erasers are alkB homolog 5 (ALKBH5) and fat mass and obesity-associated (FTO, also known as ALKBH9) proteins, which belong to ALKB family of dioxygenases [8,9]. The discovery of these specific m6A processing proteins (i.e., writers, erasers and readers), provided evidence that m6A modification is a highly regulated, reversible cellular process.

3. Regulation of m6A Writers by SAM and SAH

Similar to other typical enzymatic reactions, m6A writer-mediated methylation is dynamically regulated by substrates and products. S-adenosyl methionine (SAM/AdoMet) is a universal methyl donor for the cellular methylation processes (Figure 2A). Indeed, METTL3 was originally identified as a SAM-binding protein [5]. In cells, METTL3 forms a stable heterodimeric complex with METTL14. Even though both METTL3 and METTL14 contain methyltransferase domains (Figure 1D), the catalytic site of METTL14 lacks the SAM binding motif and only METTL3 contains enzymatic activity. Rather, METTL14 maintains METTL3–METTL14 complex stability and recruits RNA substrates for efficient m6A writing [47,48,49].
One-carbon metabolism, composed of folate and methionine cycles, is the metabolic pathway responsible for SAM production (Figure 2B). Two amino acids, serine and methionine, play key roles in providing carbons to this pathway. Serine provides a one-carbon unit to the tetrahydrofolate (THF) cofactor, generating methyl-THF. Then, another carbon acceptor, homocysteine, receives one-carbon from methyl-THF. On the other hand, methionine adenosyl transferase (MAT) produces SAM using methionine and adenosine 5′-triphosphate (ATP) as substrates. Finally, SAM provides a methyl group to adenosine on RNAs and becomes S-adenosyl homocysteine (SAH/AdoHcy). As is often the case with metabolic enzymes, the product of this methylation reaction, SAH, is a strong allosteric inhibitor of METTL3 methyltransferase activity [50] (Figure 2A).
It has been shown that the perturbation of cellular SAM levels affects DNA and histone methylation [51]. Interestingly, the Km (substrate concentration at half maximum reaction rate) of SAM for METTL3 is much lower (~100 nM) than cellular SAM levels (>10 µM) [50,52], suggesting that METTL3 is constitutively active regardless of fluctuations in cellular SAM levels. Ironically, intracellular SAH levels (~5 µM) are higher than the IC50 (half maximal inhibitory concentration) of SAH for METTL3 (~1 µM) [50,52,53], suggesting that METTL3 can also be constitutively inhibited by high SAH levels. However, it is possible that the subcellular, local concentrations of SAM and SAH are likely different from their concentrations in total cell lysates. In addition, other binding proteins of SAM or SAH can change the levels of free SAM and SAH available for METTL3. The metabolic balance of SAM and SAH in local subcellular environments and their control of METTL3 activity merits further investigation.
SAM binding affinity of m6A methyltransferase can also be regulated by substrate RNA availability. In ZCCHC4, the autoinhibitory loop interacts with the SAM-binding loop in the catalytic site, creating a closed conformation of the SAM-binding pocket [43]. This interaction is released upon 28S rRNA binding. Disruption of this intramolecular interaction by a point mutation of the autoinhibitory loop increases SAM binding affinity by four-fold, from Kd (dissociation constant) 6.7 to 1.6 µM [43]. Considering that rRNA synthesis is promoted by growth factor and nutrient-activated signaling pathways [54,55,56], it is possible that in growth-promoting conditions, increased substrate (rRNA) and methyl donor (SAM) levels cooperate for maximal rRNA methylation.
In contrast to ZCCHC4, the activity of METTL16 inversely correlates with substrate RNA binding affinity [57,58]. It has long been observed that the stability of MAT2A mRNA, which encodes SAM synthase, is increased by methionine depletion, while decreased in methionine-repleted conditions [59,60]. Pendleton et al. [57] and Shima et al. [58] defined a mechanism for methionine and the SAM-dependent regulation of MAT2A expression. When intracellular SAM levels are high, METTL16 actively methylates MAT2A mRNA and dissociates from its substrate. The m6A-modified MAT2A, which contains retained introns, is then degraded. When SAM levels are low, METTL16 tightly binds to MAT2A (without methylation) which leads to the efficient splicing of MAT2A. The spliced MAT2A mRNA is then translated into MAT2A protein, which synthesizes SAM [57,58] (Figure 1B). Therefore, SAM levels dictate METLL16 activity to exert the negative feedback regulation of de novo SAM synthesis, achieving a fine tuning of intracellular SAM levels. Whether other similar crosstalk exist between m6A enzymes and one-carbon metabolites remains unknown.

4. Metabolites Affecting m6A Erasers

4.1. TCA Cycle Metabolites

The demethylation of histones and DNA is dynamically regulated by various intracellular metabolites [51,61,62]. Likewise, metabolites also influence FTO and ALKBH5-mediated m6A RNA demethylation (Figure 2A). One example is 2-oxoglutarate (2OG, also known as alpha-ketoglutarate or αKG), the key metabolite in the citric acid cycle (tricarboxylic acid cycle, or TCA cycle) (Figure 2B). The αKG-dependent dioxygenase family proteins, which FTO and ALKBH5 belong to, require αKG, Fe(II) (non-heme iron), and O2 (molecular oxygen) for their full enzymatic activity [63,64]. Indeed, when αKG and iron binding sites in the αKG-Fe(II) oxygenase domain are mutated (Figure 1D), demethylation activities of FTO and ALKBH5 are lost [65,66].
In addition to αKG, the TCA cycle produces other metabolites that affect m6A demethylase activity (Figure 2B). αKG is oxidized and decarboxylated to produce succinate, which is further converted into fumarate. The molecular structures of succinate and fumarate are quite similar to αKG, which makes these metabolites binding competitors of αKG and thus inhibitors of m6A demethylases. However, only high concentrations of succinate and fumarate can inhibit αKG binding. In vitro, Km of αKG for ALKBH5 and FTO are 2~3 µM [50,67], whereas the IC50 of succinate and fumarate are ~30 µM (ALKBH5) and ~150 µM (FTO), respectively [65,68]. Interestingly, another key TCA cycle metabolite, citrate, was found to occupy an αKG-binding site in ALKBH5 [65]. Citrate can also be located in the αKG-binding pocket of FTO and inhibits FTO activity with IC50 ~300 µM [68].
While TCA cycle metabolites are highly compartmentalized in the mitochondria, ALKBH5 and FTO are predominantly localized in the nucleus [69,70], which may hinder TCA cycle metabolite’s influence on the m6A demethylation process. However, there is direct evidence that TCA cycle metabolites affect FTO activity in cells. R-2-hydroxyglutarate (R-2HG) is an oncometabolite produced by cancer-associated isocitrate dehydrogenase (IDH) mutants [71]. Wild type IDH catalyzes the oxidative decarboxylation of isocitrate to αKG. In contrast, mutant IDH enzymes convert αKG to R-2HG. R-2HG has been shown to structurally mimic αKG and competitively inhibit αKG-dependent dioxygenases [72]. The IC50 of R-2HG for in vitro FTO activity is ~130 µM [73]. Cellular levels of R-2HG in IDH wild-type cancer cells are less than 100 µM [74], while IDH mutants increase R-2HG levels up to ~1000 fold in cell lines and patients [75,76,77]. The treatment of R-2HG (~300 µM) or ectopic expression of IDH mutants increased cellular m6A levels [73,75]. Surprisingly, R-2HG suppressed the growth of tumors expressing high FTO levels. Specifically, the R-2HG-induced m6A modification of cMyc and CEBPA mRNAs destabilized these transcripts. Therefore, by decreasing the growth-promoting cMyc and CEBP signaling activities, R-2HG suppresses tumor progression [73]. This anti-tumor activity of R-2HG was unexpected and the opposite of its oncometabolite, tumor-initiating function. This example reflects the complex nature of metabolite-mediated regulation of cellular processes and emphasizes the importance of elucidating context-dependent metabolite effects, including the unexplored area of m6A modifications.

4.2. Iron

The activation of oxygen by iron is essential for the oxidative demethylation reaction by αKG-Fe(II)-dependent dioxygenases [63,64] (Figure 2A). Indeed, iron depletion in mice and cells by diet alternation and iron chelation led to decreased histone demethylase activity [78,79]. The Km of Fe(II) for ALKBH5 is ~1 µM [50]. This is within the range of free cellular Fe(II) (1~3 µM) [80], indicating that perturbations in cellular iron levels may affect m6A modification. Major organelles regulating iron metabolism are the lysosome and mitochondria [81] (Figure 2B). In mammals, the main means of iron uptake is via the transferrin–iron complex. The internalized transferrin–iron complex is delivered to the lysosome through endocytosis pathways where iron is then liberated from transferrin by low lysosomal pH and released into the cytoplasm. Therefore, the dysregulation of lysosomal acidification can potentially decrease m6A demethylase activity. Although there is no such direct study, iron-dependent ribosome recycling has been shown to decrease the expression of m6A-containing mRNAs [82]. Once released into the cytoplasm, free iron is transported into mitochondria through mitoferrin transporters [81]. Mitochondria consumes lots of iron in the production of iron–sulfur clusters and reactive oxygen species, and thus their dysfunction impairs iron homeostasis. Future investigations about how lysosomal and mitochondrial iron metabolism influences m6A RNA modification will provide insights not only for m6A metabolism but also for iron deficiency-induced human diseases.

4.3. NADP(H)

In a recent study, Wang et al. found that nicotinamide adenine dinucleotide (NAD) and nicotinamide adenine dinucleotide phosphate (NADP) increase FTO activity [83] (Figure 2A). Using the florescence quenching assay of FTO, they screened metabolites that directly bind to FTO. From the screen, NADH and NADPH were identified, along with vitamin C (ascorbate), a previously known cofactor of dioxygenases. Although the NAD derivatives (NAD+, NADH, NADP+ and NADPH) are structurally similar, NADPH was the strongest binding partner and activator of FTO, followed by NADH. This indicates that the reducing potential of NADPH and NADH may be used for demethylation reactions. Nonetheless, NADPH was not consumed by FTO, and the concentration remained constant during demethylation. Interestingly, the induction of m6A demethylase activity by NADPH occurred less in ALKBH5 (~30% induction in ALKBH5 vs. ~90% induction in FTO). Further mechanistic studies will be required to better understand the underlying mechanisms of NADPH-dependent activation of m6A demethylases.
The pentose phosphate pathway (PPP) is the major source of NADPH [84] (Figure 2B). Branched from glycolysis, PPP uses glucose-6-phosphate (G6P) as a primary substrate. G6P dehydrogenase (G6PD), the rate limiting enzyme in PPP, oxidizes G6P into 6-phosphogluconolactone while reducing NADP+ to NADPH. NADPH is a key reducing agent for cellular biosynthetic processes, such as fat synthesis. The knockdown of NAD kinase (NADK) and G6PD increased cellular m6A levels, which was decreased by NADPH supplementation. Conversely, the induction of NADPH levels by high-fat diet or glucose injection, decreased m6A levels [83], indicating that FTO-dependent m6A demethylation may be involved in the biological processes regulated by NADPH.
Indeed, the inhibition of FTO increased the m6A modification of the genes involved in adipocyte differentiation and blocked NADPH-induced adipogenesis [83]. Fto knockout mice are resistant to high-fat diet-induced obesity, while the overexpression of Fto results in obesity [83,85,86,87]. Given that FTO polymorphism is associated with various human metabolic diseases, including obesity, diabetes, and cardiovascular disease [88,89], it will be interesting to study how FTO and NADPH-dependent m6A demethylation contributes to metabolic processes in normal and pathological conditions.

5. Conclusions Remarks and Future Directions

Emerging evidence has implied the involvement of metabolites and metabolic pathways in m6A RNA modification. To better understand this important interplay in physiological and pathological contexts, more investigations are needed at the organismal level. For example, methionine is the key amino acid for SAM production. It will be interesting if a low methionine diet, which increases life span and enhances cancer treatment responses [90,91], works by decreasing the activity of specific m6A RNA methyltransferases. Additionally, it has been shown that m6A levels are different in various tissues. In mice, the brain, liver, and kidney contain more m6A than heart and lung. However, the expression levels of m6A writers and erasers only partially correlate with tissue-specific m6A levels [10,92]. It is possible that the metabolic activities of each organ determine the actual enzyme activities by limiting substrate and cofactor levels.
In addition to directly responding to nutrient levels, the activity of metabolic pathways is also governed by signal transduction pathways. As a master regulator of cell growth, the mechanistic target of rapamycin (mTORC1) controls the expression and activity of numerous enzymes in the metabolic pathways discussed in this review [93,94,95]. The great strides in cancer metabolism research over the past few decades have also elucidated a direct and close connection between metabolic enzymes and nutrient signaling pathways, including phosphoinositide 3-kinase (PI3K)-Akt, Ras-ERK, and AMPK [96,97,98,99]. It will be exciting to explore how these nutrient-signaling networks regulate m6A RNA methylation. Given that several small molecule inhibitors for m6A enzymes have been developed for oncological applications [100], the combined targeting of cancer metabolism and signaling with m6A modification enzymes could provide a new strategy for cancer therapeutics.
Another unexplored area is the metabolic regulation of m6A readers. The m6A writer, METTL3, possesses m6A reader function [101]. While it writes m6A in the nucleus, in the cytoplasm it binds to m6A-modified mRNA and increases target mRNA’s translation efficiency. Whether SAM or SAH, the metabolites that affect METTL3′s m6A writer function, can also influence METTL3′s reader function is not known. Intriguingly, some m6A reader proteins, specifically the YTHDF family, form liquid droplets through phase separation [46], which is also often formed by metabolic enzymes [102,103]. This implicates a potential interaction between metabolic enzymes and m6A readers by physical proximity. Protein interactome analysis of m6A readers, as well as protein–metabolite interaction screens, such as cellular thermal shift assay (CETSA) [104] and drug affinity responsive target stability (DARTS) [105], will provide useful information to identify new competitive and allosteric regulators of m6A readers. Since readers are actual effector proteins that determine the fates of m6A-modified RNAs, m6A reader proteins can be a way of controlling specific genes using metabolites.
In addition to m6A, RNA contains more than 100 different types of chemical modifications, including di- and tri-methylations, acetylation, deamination, thiolation (sulfuration), oxidation, and even glycosylation [106], which should be tightly regulated under dynamic environmental changes and cell status. Comprehensive understanding of how nutrients and metabolic pathways orchestrate the diverse array of RNA chemical modifications will provide new insights in the field of RNA epitranscriptomics, nutrient signaling, and metabolism.

Funding

This research received no external funding.

Acknowledgments

We thank Lavina Mathur, Sunhee Jung, Johnny Le, Yasmine Alam, and Cholsoon Jang for scientific discussion and helpful comments. We apologize to authors whose work was not cited due to space limitations.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Gott, J.M.; Emeson, R.B. Functions and mechanisms of RNA editing. Annu. Rev. Genet. 2000, 34, 499–531. [Google Scholar] [CrossRef] [PubMed]
  2. Gilbert, W.V.; Bell, T.A.; Schaening, C. Messenger RNA modifications: Form, distribution, and function. Science 2016, 352, 1408–1412. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Desrosiers, R.; Friderici, K.; Rottman, F. Identification of methylated nucleosides in messenger RNA from Novikoff hepatoma cells. Proc. Natl. Acad. Sci. USA 1974, 71, 3971–3975. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Perry, R.P.; Kelley, D.E. Existence of methylated messenger RNA in mouse L cells. Cell 1974, 1, 37–42. [Google Scholar] [CrossRef]
  5. Bokar, J.A.; Shambaugh, M.E.; Polayes, D.; Matera, A.G.; Rottman, F.M. Purification and cDNA cloning of the AdoMet-binding subunit of the human mRNA (N6-adenosine)-methyltransferase. Rna 1997, 3, 1233–1247. [Google Scholar] [PubMed]
  6. Bujnicki, J.M.; Feder, M.; Radlinska, M.; Blumenthal, R.M. Structure prediction and phylogenetic analysis of a functionally diverse family of proteins homologous to the MT-A70 subunit of the human mRNA:m6A methyltransferase. J. Mol. Evol. 2002, 55, 431–444. [Google Scholar] [CrossRef]
  7. Liu, J.; Yue, Y.; Han, D.; Wang, X.; Fu, Y.; Zhang, L.; Jia, G.; Yu, M.; Lu, Z.; Deng, X.; et al. A METTL3-METTL14 complex mediates mammalian nuclear RNA N6-adenosine methylation. Nat. Chem. Biol. 2014, 10, 93–95. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Jia, G.; Fu, Y.; Zhao, X.; Dai, Q.; Zheng, G.; Yang, Y.; Yi, C.; Lindahl, T.; Pan, T.; Yang, Y.G.; et al. N6-Methyladenosine in nuclear RNA is a major substrate of the obesity-associated FTO. Nat. Chem. Biol. 2011, 7, 885–887. [Google Scholar] [CrossRef]
  9. Zheng, G.; Dahl, J.A.; Niu, Y.; Fedorcsak, P.; Huang, C.M.; Li, C.J.; Vågbø, C.B.; Shi, Y.; Wang, W.L.; Song, S.H.; et al. ALKBH5 Is a Mammalian RNA Demethylase that Impacts RNA Metabolism and Mouse Fertility. Mol. Cell 2013, 49, 18–29. [Google Scholar] [CrossRef] [Green Version]
  10. Meyer, K.D.; Saletore, Y.; Zumbo, P.; Elemento, O.; Mason, C.E.; Jaffrey, S.R. Comprehensive analysis of mRNA methylation reveals enrichment in 3′ UTRs and near stop codons. Cell 2012, 149, 1635–1646. [Google Scholar] [CrossRef] [Green Version]
  11. Dominissini, D.; Moshitch-Moshkovitz, S.; Schwartz, S.; Salmon-Divon, M.; Ungar, L.; Osenberg, S.; Cesarkas, K.; Jacob-Hirsch, J.; Amariglio, N.; Kupiec, M.; et al. Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature 2012, 485, 201–206. [Google Scholar] [CrossRef] [PubMed]
  12. Zhou, K.I.; Parisien, M.; Dai, Q.; Liu, N.; Diatchenko, L.; Sachleben, J.R.; Pan, T. N6-Methyladenosine Modification in a Long Noncoding RNA Hairpin Predisposes Its Conformation to Protein Binding. J. Mol. Biol. 2016, 428, 822–833. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Patil, D.P.; Chen, C.K.; Pickering, B.F.; Chow, A.; Jackson, C.; Guttman, M.; Jaffrey, S.R. m(6)A RNA methylation promotes XIST-mediated transcriptional repression. Nature 2016, 537, 369–373. [Google Scholar] [CrossRef] [PubMed]
  14. Van Tran, N.; Ernst, F.G.M.; Hawley, B.R.; Zorbas, C.; Ulryck, N.; Hackert, P.; Bohnsack, K.E.; Bohnsack, M.T.; Jaffrey, S.R.; Graille, M.; et al. The human 18S rRNA m6A methyltransferase METTL5 is stabilized by TRMT112. Nucleic Acids Res. 2019, 47, 7719–7733. [Google Scholar] [CrossRef] [Green Version]
  15. Ma, H.; Wang, X.; Cai, J.; Dai, Q.; Natchiar, S.K.; Lv, R.; Chen, K.; Lu, Z.; Chen, H.; Shi, Y.G.; et al. N 6-Methyladenosine methyltransferase ZCCHC4 mediates ribosomal RNA methylation. Nat. Chem. Biol. 2019, 15, 88–94. [Google Scholar] [CrossRef]
  16. Mauer, J.; Sindelar, M.; Despic, V.; Guez, T.; Hawley, B.R.; Vasseur, J.J.; Rentmeister, A.; Gross, S.S.; Pellizzoni, L.; Debart, F.; et al. FTO controls reversible m6Am RNA methylation during snRNA biogenesis. Nat. Chem. Biol. 2019, 15, 340–347. [Google Scholar] [CrossRef]
  17. Aoyama, T.; Yamashita, S.; Tomita, K. Mechanistic insights into m6A modification of U6 snRNA by human METTL16. Nucleic Acids Res. 2020, 48, 5157–5168. [Google Scholar] [CrossRef]
  18. Kasowitz, S.D.; Ma, J.; Anderson, S.J.; Leu, N.A.; Xu, Y.; Gregory, B.D.; Schultz, R.M.; Wang, P.J. Nuclear m6A reader YTHDC1 regulates alternative polyadenylation and splicing during mouse oocyte development. PLoS Genet. 2018, 14, 1–28. [Google Scholar] [CrossRef]
  19. Sommer, S.; Lavi, U.; Darnell, J.E. The absolute frequency of labeled N-6-methyladenosine in HeLa cell messenger RNA decreases with label time. J. Mol. Biol. 1978, 124, 487–499. [Google Scholar] [CrossRef]
  20. Huang, H.; Weng, H.; Sun, W.; Qin, X.; Shi, H.; Wu, H.; Zhao, B.S.; Mesquita, A.; Liu, C.; Yuan, C.L.; et al. Recognition of RNA N6-methyladenosine by IGF2BP proteins enhances mRNA stability and translation. Nat. Cell Biol. 2018, 20, 285–295. [Google Scholar] [CrossRef]
  21. Wang, X.; Lu, Z.; Gomez, A.; Hon, G.C.; Yue, Y.; Han, D.; Fu, Y.; Parisien, M.; Dai, Q.; Jia, G.; et al. N 6-methyladenosine-dependent regulation of messenger RNA stability. Nature 2014, 505, 117–120. [Google Scholar] [CrossRef] [PubMed]
  22. Roundtree, I.A.; Luo, G.Z.; Zhang, Z.; Wang, X.; Zhou, T.; Cui, Y.; Sha, J.; Huang, X.; Guerrero, L.; Xie, P.; et al. YTHDC1 mediates nuclear export of N6-methyladenosine methylated mRNAs. Elife 2017, 6, 1–28. [Google Scholar] [CrossRef] [PubMed]
  23. Wang, X.; Zhao, B.S.; Roundtree, I.A.; Lu, Z.; Han, D.; Ma, H.; Weng, X.; Chen, K.; Shi, H.; He, C. N(6)-methyladenosine modulates messenger RNA translation efficiency. Cell 2015, 161, 1388–1399. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Meyer, K.D.; Patil, D.P.; Zhou, J.; Zinoviev, A.; Skabkin, M.A.; Elemento, O.; Pestova, T.V.; Qian, S.B.; Jaffrey, S.R. 5′ UTR m6A Promotes Cap-Independent Translation. Cell 2015, 163, 999–1010. [Google Scholar] [CrossRef] [Green Version]
  25. Batista, P.J.; Molinie, B.; Wang, J.; Qu, K.; Zhang, J.; Li, L.; Bouley, D.M.; Lujan, E.; Haddad, B.; Daneshvar, K.; et al. M6A RNA modification controls cell fate transition in mammalian embryonic stem cells. Cell Stem Cell 2014, 15, 707–719. [Google Scholar] [CrossRef] [Green Version]
  26. Geula, S.; Moshitch-Moshkovitz, S.; Dominissini, D.; Mansour, A.A.F.; Kol, N.; Salmon-Divon, M.; Hershkovitz, V.; Peer, E.; Mor, N.; Manor, Y.S.; et al. m6A mRNA methylation facilitates resolution of naïve pluripotency toward differentiation. Science 2015, 347, 1002–1006. [Google Scholar] [CrossRef]
  27. Li, M.; Zhao, X.; Wang, W.; Shi, H.; Pan, Q.; Lu, Z.; Perez, S.P.; Suganthan, R.; He, C.; Bjørås, M.; et al. Ythdf2-mediated m6A mRNA clearance modulates neural development in mice. Genome Biol. 2018, 19, 1–16. [Google Scholar] [CrossRef] [Green Version]
  28. Yoon, K.J.; Ringeling, F.R.; Vissers, C.; Jacob, F.; Pokrass, M.; Jimenez-Cyrus, D.; Su, Y.; Kim, N.S.; Zhu, Y.; Zheng, L.; et al. Temporal Control of Mammalian Cortical Neurogenesis by m6A Methylation. Cell 2017, 171, 877–889.e17. [Google Scholar] [CrossRef] [Green Version]
  29. Barbieri, I.; Tzelepis, K.; Pandolfini, L.; Shi, J.; Millán-Zambrano, G.; Robson, S.C.; Aspris, D.; Migliori, V.; Bannister, A.J.; Han, N.; et al. Promoter-bound METTL3 maintains myeloid leukaemia by m6A-dependent translation control. Nature 2017, 552, 126–131. [Google Scholar] [CrossRef]
  30. Vu, L.P.; Pickering, B.F.; Cheng, Y.; Zaccara, S.; Nguyen, D.; Minuesa, G.; Chou, T.; Chow, A.; Saletore, Y.; Mackay, M.; et al. The N 6 -methyladenosine (m 6 A)-forming enzyme METTL3 controls myeloid differentiation of normal hematopoietic and leukemia cells. Nat. Med. 2017, 23, 1369–1376. [Google Scholar] [CrossRef]
  31. Weng, H.; Huang, H.; Wu, H.; Qin, X.; Zhao, B.S.; Dong, L.; Shi, H.; Skibbe, J.; Shen, C.; Hu, C.; et al. METTL14 Inhibits Hematopoietic Stem/Progenitor Differentiation and Promotes Leukemogenesis via mRNA m6A Modification. Cell Stem Cell 2018, 22, 191–205.e9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. De Jesus, D.F.; Zhang, Z.; Kahraman, S.; Brown, N.K.; Chen, M.; Hu, J.; Gupta, M.K.; He, C.; Kulkarni, R.N. m6A mRNA methylation regulates human β-cell biology in physiological states and in type 2 diabetes. Nat. Metab. 2019, 1, 765–774. [Google Scholar] [CrossRef] [PubMed]
  33. Yang, Y.; Shen, F.; Huang, W.; Qin, S.; Huang, J.T.; Sergi, C.; Yuan, B.F.; Liu, S.M. Glucose Is Involved in the Dynamic Regulation of m 6 A in Patients with Type 2 Diabetes. J. Clin. Endocrinol. Metab. 2018, 104, 665–673. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Fu, Y.; Dominissini, D.; Rechavi, G.; He, C. Gene expression regulation mediated through reversible m6A RNA methylation. Nat. Rev. Genet. 2014, 15, 293–306. [Google Scholar] [CrossRef] [PubMed]
  35. Huang, H.; Weng, H.; Chen, J. m6A Modification in Coding and Non-coding RNAs: Roles and Therapeutic Implications in Cancer. Cancer Cell 2020, 37, 270–288. [Google Scholar] [CrossRef]
  36. Barbieri, I.; Kouzarides, T. Role of RNA modifications in cancer. Nat. Rev. Cancer 2020, 20, 303–322. [Google Scholar] [CrossRef]
  37. Zaccara, S.; Ries, R.J.; Jaffrey, S.R. Reading, writing and erasing mRNA methylation. Nat. Rev. Mol. Cell Biol. 2019, 20, 608–624. [Google Scholar] [CrossRef]
  38. Liu, J.; Yue, Y.; Liu, J.; Cui, X.; Cao, J.; Luo, G.; Zhang, Z.; Cheng, T.; Gao, M.; Shu, X.; et al. VIRMA mediates preferential m6A mRNA methylation in 3′UTR and near stop codon and associates with alternative polyadenylation. Cell Discov. 2018, 4, 1–17. [Google Scholar]
  39. Wen, J.; Lv, R.; Ma, H.; Shen, H.; He, C.; Wang, J.; Jiao, F.; Liu, H.; Yang, P.; Tan, L.; et al. Zc3h13 Regulates Nuclear RNA m6A Methylation and Mouse Embryonic Stem Cell Self-Renewal. Mol. Cell 2018, 69, 1028–1038. [Google Scholar] [CrossRef] [Green Version]
  40. Warda, A.S.; Kretschmer, J.; Hackert, P.; Lenz, C.; Urlaub, H.; Höbartner, C.; Sloan, K.E.; Bohnsack, M.T. Human METTL16 is a N6 -methyladenosine (m6A) methyltransferase that targets pre-mRNAs and various non-coding RNAs. EMBO Rep. 2017, 18, 2004–2014. [Google Scholar] [CrossRef]
  41. Mendel, M.; Chen, K.M.; Homolka, D.; Gos, P.; Pandey, R.R.; McCarthy, A.A.; Pillai, R.S. Methylation of Structured RNA by the m6A Writer METTL16 Is Essential for Mouse Embryonic Development. Mol. Cell 2018, 71, 986–1000.e11. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Ruszkowska, A.; Ruszkowski, M.; Dauter, Z.; Brown, J.A. Structural insights into the RNA methyltransferase domain of METTL16. Sci. Rep. 2018, 8, 1–13. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Ren, W.; Lu, J.; Huang, M.; Gao, L.; Li, D.; Greg Wang, G.; Song, J. Structure and regulation of ZCCHC4 in m6A-methylation of 28S rRNA. Nat. Commun. 2019, 10, 1–9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Patil, D.P.; Pickering, B.F.; Jaffrey, S.R. Reading m6A in the Transcriptome: m6A-Binding Proteins. Trends Cell Biol. 2018, 28, 113–127. [Google Scholar] [CrossRef]
  45. Liu, N.; Dai, Q.; Zheng, G.; He, C.; Parisien, M.; Pan, T. N(6) -methyladenosine-dependent RNA structural switches regulate RNA-protein interactions. Nature 2015, 518, 560–564. [Google Scholar] [CrossRef] [Green Version]
  46. Ries, R.J.; Zaccara, S.; Klein, P.; Olarerin-George, A.; Namkoong, S.; Pickering, B.F.; Patil, D.P.; Kwak, H.; Lee, J.H.; Jaffrey, S.R. m6A enhances the phase separation potential of mRNA. Nature 2019, 571, 424–428. [Google Scholar] [CrossRef]
  47. Śledź, P.; Jinek, M. Structural insights into the molecular mechanism of the m(6)A writer complex. Elife 2016, 5, 1–16. [Google Scholar] [CrossRef]
  48. Wang, X.; Feng, J.; Xue, Y.; Guan, Z.; Zhang, D.; Liu, Z.; Gong, Z.; Wang, Q.; Huang, J.; Tang, C.; et al. Structural basis of N(6)-adenosine methylation by the METTL3-METTL14 complex. Nature 2016, 534, 575–578. [Google Scholar] [CrossRef]
  49. Wang, P.; Doxtader, K.A.; Nam, Y. Structural Basis for Cooperative Function of Mettl3 and Mettl14 Methyltransferases. Mol. Cell 2016, 63, 306–317. [Google Scholar] [CrossRef] [Green Version]
  50. Li, F.; Kennedy, S.; Hajian, T.; Gibson, E.; Seitova, A.; Xu, C.; Arrowsmith, C.H.; Vedadi, M. A Radioactivity-Based Assay for Screening Human m6A-RNA Methyltransferase, METTL3-METTL14 Complex, and Demethylase ALKBH5. J. Biomol. Screen. 2016, 21, 290–297. [Google Scholar] [CrossRef] [Green Version]
  51. Reid, M.A.; Dai, Z.; Locasale, J.W. The impact of cellular metabolism on chromatin dynamics and epigenetics. Nat. Cell Biol. 2017, 19, 1298–1306. [Google Scholar] [CrossRef] [PubMed]
  52. Duncan, T.M.; Reed, M.C.; Nijhout, H.F. The relationship between intracellular and plasma levels of folate and metabolites in the methionine cycle: A model. Mol. Nutr. Food Res. 2013, 57, 628–636. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Selberg, S.; Blokhina, D.; Aatonen, M.; Koivisto, P.; Siltanen, A.; Mervaala, E.; Kankuri, E.; Karelson, M. Discovery of Small Molecules that Activate RNA Methylation through Cooperative Binding to the METTL3-14-WTAP Complex Active Site. Cell Rep. 2019, 26, 3762–3771. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Nguyen, L.X.T.; Mitchell, B.S. Akt activation enhances ribosomal RNA synthesis through casein kinase II and TIF-IA. Proc. Natl. Acad. Sci. USA 2013, 110, 20681–20686. [Google Scholar] [CrossRef] [Green Version]
  55. Gomez-Roman, N.; Grandori, C.; Eisenman, R.N.; White, R.J. Direct activation of RNA polymerase III transcription by c-Myc. Nature 2003, 421, 290–294. [Google Scholar] [CrossRef]
  56. Iadevaia, V.; Zhang, Z.; Jan, E.; Proud, C.G. mTOR signaling regulates the processing of pre-rRNA in human cells. Nucleic Acids Res. 2012, 40, 2527–2539. [Google Scholar] [CrossRef]
  57. Pendleton, K.E.; Chen, B.; Liu, K.; Hunter, O.V.; Xie, Y.; Tu, B.P.; Conrad, N.K. The U6 snRNA m6A Methyltransferase METTL16 Regulates SAM Synthetase Intron Retention. Cell 2017, 169, 824–835. [Google Scholar] [CrossRef] [Green Version]
  58. Shima, H.; Matsumoto, M.; Ishigami, Y.; Ebina, M.; Muto, A.; Sato, Y.; Kumagai, S.; Ochiai, K.; Suzuki, T.; Igarashi, K. S-Adenosylmethionine Synthesis Is Regulated by Selective N6-Adenosine Methylation and mRNA Degradation Involving METTL16 and YTHDC1. Cell Rep. 2017, 21, 3354–3363. [Google Scholar] [CrossRef] [Green Version]
  59. Martínez-Chantar, M.L.; Latasa, M.U.; Varela-Rey, M.; Lu, S.C.; García-Trevijano, E.R.; Mato, J.M.; Avila, M.A. L-methionine availability regulates expression of the methionine adenosyltransferase 2A gene in human hepatocarcinoma cells. Role of S-adenosylmethionine. J. Biol. Chem. 2003, 278, 19885–19890. [Google Scholar] [CrossRef] [Green Version]
  60. Bresson, S.M.; Hunter, O.V.; Hunter, A.C.; Conrad, N.K. Canonical Poly(A) Polymerase Activity Promotes the Decay of a Wide Variety of Mammalian Nuclear RNAs. PLoS Genet. 2015, 11, 1–25. [Google Scholar] [CrossRef] [Green Version]
  61. Schvartzman, J.M.; Thompson, C.B.; Finley, L.W.S. Metabolic regulation of chromatin modifications and gene expression. J. Cell Biol. 2018, 217, 2247–2259. [Google Scholar] [CrossRef] [PubMed]
  62. Campbell, S.L.; Wellen, K.E. Metabolic Signaling to the Nucleus in Cancer. Mol. Cell 2018, 71, 398–408. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Xu, G.L.; Bochtler, M. Reversal of nucleobase methylation by dioxygenases. Nat. Chem. Biol. 2020, 16, 1160–1169. [Google Scholar] [CrossRef]
  64. Losman, J.A.; Koivunen, P.; Kaelin, W.G. 2-Oxoglutarate-dependent dioxygenases in cancer. Nat. Rev. Cancer 2020, 20, 710–726. [Google Scholar] [CrossRef] [PubMed]
  65. Feng, C.; Liu, Y.; Wang, G.; Deng, Z.; Zhang, Q.; Wu, W.; Tong, Y.; Cheng, C.; Chen, Z. Crystal structures of the human RNA demethylase alkbh5 reveal basis for substrate recognition. J. Biol. Chem. 2014, 289, 11571–11583. [Google Scholar] [CrossRef] [Green Version]
  66. Zhang, X.; Wei, L.H.; Wang, Y.; Xiao, Y.; Liu, J.; Zhang, W.; Yan, N.; Amu, G.; Tang, X.; Zhang, L.; et al. Structural insights into FTO’s catalytic mechanism for the demethylation of multiple RNA substrates. Proc. Natl. Acad. Sci. USA 2019, 116, 2919–2924. [Google Scholar] [CrossRef] [Green Version]
  67. Ma, M.; Harding, H.P.; O’Rahilly, S.; Ron, D.; Yeo, G.S.H. Kinetic analysis of FTO (fat mass and obesity-associated) reveals that it is unlikely to function as a sensor for 2-oxoglutarate. Biochem. J. 2012, 444, 183–187. [Google Scholar] [CrossRef] [Green Version]
  68. Aik, W.; Demetriades, M.; Hamdan, M.K.K.; Bagg, E.A.L.; Yeoh, K.K.; Lejeune, C.; Zhang, Z.; McDonough, M.A.; Schofield, C.J. Structural basis for inhibition of the fat mass and obesity associated protein (FTO). J. Med. Chem. 2013, 56, 3680–3688. [Google Scholar] [CrossRef]
  69. Tang, C.; Klukovich, R.; Peng, H.; Wang, Z.; Yu, T.; Zhang, Y.; Zheng, H.; Klungland, A.; Yan, W. ALKBH5-dependent m6A demethylation controls splicing and stability of long 3’-UTR mRNAs in male germ cells. Proc. Natl. Acad. Sci. USA 2017, 115, E325–E333. [Google Scholar] [CrossRef] [Green Version]
  70. Gulati, P.; Avezov, E.; Ma, M.; Antrobus, R.; Lehner, P.; O’Rahilly, S.; Yeo, G.S.H. Fat mass and obesity-related (FTO) shuttles between the nucleus and cytoplasm. Biosci. Rep. 2014, 34, 621–628. [Google Scholar] [CrossRef]
  71. Dang, L.; White, D.W.; Gross, S.; Bennett, B.D.; Bittinger, M.A.; Driggers, E.M.; Fantin, V.R.; Jang, H.G.; Jin, S.; Keenan, M.C.; et al. Cancer-associated IDH1 mutations produce 2-hydroxyglutarate. Nature 2009, 462, 739–744. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  72. Xu, W.; Yang, H.; Liu, Y.; Yang, Y.; Wang, P.; Kim, S.H.; Ito, S.; Yang, C.; Wang, P.; Xiao, M.T.; et al. Oncometabolite 2-hydroxyglutarate is a competitive inhibitor of α-ketoglutarate-dependent dioxygenases. Cancer Cell 2011, 19, 17–30. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  73. Su, R.; Dong, L.; Li, C.; Nachtergaele, S.; Wunderlich, M.; Qing, Y.; Deng, X.; Wang, Y.; Weng, X.; Hu, C.; et al. R-2HG Exhibits Anti-tumor Activity by Targeting FTO/m6A/MYC/CEBPA Signaling. Cell 2018, 172, 90–105.e23. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  74. Fan, J.; Teng, X.; Liu, L.; Mattaini, K.R.; Looper, R.E.; Vander Heiden, M.G.; Rabinowitz, J.D. Human phosphoglycerate dehydrogenase produces the oncometabolite D-2-hydroxyglutarate. ACS Chem. Biol. 2015, 10, 510–516. [Google Scholar] [CrossRef] [PubMed]
  75. Elkashef, S.M.; Lin, A.P.; Myers, J.; Sill, H.; Jiang, D.; Dahia, P.L.M.; Aguiar, R.C.T. IDH Mutation, Competitive Inhibition of FTO, and RNA Methylation. Cancer Cell 2017, 31, 619–620. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  76. DiNardo, C.D.; Propert, K.J.; Loren, A.W.; Paietta, E.; Sun, Z.; Levine, R.L.; Straley, K.S.; Yen, K.; Patel, J.P.; Agresta, S.; et al. Serum 2-hydroxyglutarate levels predict isocitrate dehydrogenase mutations and clinical outcome in acute myeloid leukemia. Blood 2013, 121, 4917–4924. [Google Scholar] [CrossRef]
  77. Suh, C.H.; Kim, H.S.; Jung, S.C.; Choi, C.G.; Kim, S.J. 2-Hydroxyglutarate MR spectroscopy for prediction of isocitrate dehydrogenase mutant glioma: A systemic review and meta-analysis using individual patient data. Neuro-Oncol. 2018, 20, 1573–1583. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  78. Pogribny, I.P.; Tryndyak, V.P.; Pogribna, M.; Shpyleva, S.; Surratt, G.; Da Costa, G.G.; Beland, F.A. Modulation of intracellular iron metabolism by iron chelation affects chromatin remodeling proteins and corresponding epigenetic modifications in breast cancer cells and increases their sensitivity to chemotherapeutic agents. Int. J. Oncol. 2013, 42, 1822–1832. [Google Scholar] [CrossRef] [Green Version]
  79. Jiang, Y.; Li, C.; Wu, Q.; An, P.; Huang, L.; Wang, J.; Chen, C.; Chen, X.; Zhang, F.; Ma, L.; et al. Iron-dependent histone 3 lysine 9 demethylation controls B cell proliferation and humoral immune responses. Nat. Commun. 2019, 10, 1–15. [Google Scholar] [CrossRef] [Green Version]
  80. Recalcati, S.; Gammella, E.; Buratti, P.; Cairo, G. Molecular regulation of cellular iron balance. IUBMB Life 2017, 69, 389–398. [Google Scholar] [CrossRef] [Green Version]
  81. Crielaard, B.J.; Lammers, T.; Rivella, S. Targeting iron metabolism in drug discovery and delivery. Nat. Rev. Drug Discov. 2017, 16, 400–423. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  82. Zhu, X.; Zhang, H.; Mendell, J.T. Ribosome Recycling by ABCE1 Links Lysosomal Function and Iron Homeostasis to 3’ UTR-Directed Regulation and Nonsense-Mediated Decay. Cell Rep. 2020, 32, 107895. [Google Scholar] [CrossRef] [PubMed]
  83. Wang, L.; Song, C.; Wang, N.; Li, S.; Liu, Q.; Sun, Z.; Wang, K.; Yu, S.C.; Yang, Q. NADP modulates RNA m6A methylation and adipogenesis via enhancing FTO activity. Nat. Chem. Biol. 2020, 16, 1394–1402. [Google Scholar] [CrossRef] [PubMed]
  84. Chen, L.; Zhang, Z.; Hoshino, A.; Zheng, H.D.; Morley, M.; Arany, Z.; Rabinowitz, J.D. NADPH production by the oxidative pentose-phosphate pathway supports folate. Nat. Metab. 2019, 1, 404–415. [Google Scholar] [CrossRef] [PubMed]
  85. Fischer, J.; Koch, L.; Emmerling, C.; Vierkotten, J.; Peters, T.; Brüning, J.C.; Rüther, U. Inactivation of the Fto gene protects from obesity. Nature 2009, 458, 894–898. [Google Scholar] [CrossRef]
  86. Gao, X.; Shin, Y.H.; Li, M.; Wang, F.; Tong, Q.; Zhang, P. The fat mass and obesity associated gene FTO functions in the brain to regulate postnatal growth in mice. PLoS ONE 2010, 5, e14005. [Google Scholar] [CrossRef] [Green Version]
  87. Church, C.; Moir, L.; McMurray, F.; Girard, C.; Banks, G.T.; Teboul, L.; Wells, S.; Brüning, J.C.; Nolan, P.M.; Ashcroft, F.M.; et al. Overexpression of Fto leads to increased food intake and results in obesity. Nat. Genet. 2010, 42, 1086–1092. [Google Scholar] [CrossRef]
  88. Thorleifsson, G.; Walters, G.B.; Gudbjartsson, D.F.; Steinthorsdottir, V.; Sulem, P.; Helgadottir, A.; Styrkarsdottir, U.; Gretarsdottir, S.; Thorlacius, S.; Jonsdottir, I.; et al. Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity. Nat. Genet. 2009, 41, 18–24. [Google Scholar] [CrossRef]
  89. Frayling, T.M. Genome-wide association studies provide new insights into type 2 diabetes aetiology. Nat. Rev. Genet. 2007, 8, 657–662. [Google Scholar] [CrossRef]
  90. Orentreich, N.; Matias, J.R.; DeFelice, A.; Zimmerman, J.A. Low methionine ingestion by rats extends life span. J. Nutr. 1993, 123, 269–274. [Google Scholar]
  91. Gao, X.; Sanderson, S.M.; Dai, Z.; Reid, M.A.; Cooper, D.E.; Lu, M.; Richie, J.P.; Ciccarella, A.; Calcagnotto, A.; Mikhael, P.G.; et al. Dietary methionine influences therapy in mouse cancer models and alters human metabolism. Nature 2019, 572, 397–401. [Google Scholar] [CrossRef] [PubMed]
  92. Liu, J.; Li, K.; Cai, J.; Zhang, M.; Zhang, X.; Xiong, X.; Meng, H.; Xu, X.; Huang, Z.; Peng, J.; et al. Landscape and Regulation of m6A and m6Am Methylome across Human and Mouse Tissues. Mol. Cell 2020, 77, 426–440.e6. [Google Scholar] [CrossRef] [PubMed]
  93. Saxton, R.A.; Sabatini, D.M. mTOR Signaling in Growth, Metabolism, and Disease. Cell 2017, 169, 361–371. [Google Scholar] [CrossRef] [PubMed]
  94. Shimobayashi, M.; Hall, M.N. Making new contacts: The mTOR network in metabolism and signalling crosstalk. Nat. Rev. Mol. Cell Biol. 2014, 15, 155–162. [Google Scholar] [CrossRef] [PubMed]
  95. Valvezan, A.J.; Manning, B.D. Molecular logic of mTORC1 signalling as a metabolic rheostat. Nat. Metab. 2019, 1, 321–333. [Google Scholar] [CrossRef]
  96. Pavlova, N.N.; Thompson, C.B. The Emerging Hallmarks of Cancer Metabolism. Cell Metab. 2016, 23, 27–47. [Google Scholar] [CrossRef] [Green Version]
  97. Hoxhaj, G.; Manning, B.D. The PI3K–AKT network at the interface of oncogenic signalling and cancer metabolism. Nat. Rev. Cancer 2020, 20, 74–88. [Google Scholar] [CrossRef]
  98. Vander Heiden, M.G.; DeBerardinis, R.J. Understanding the Intersections between Metabolism and Cancer Biology. Cell 2017, 168, 657–669. [Google Scholar] [CrossRef] [Green Version]
  99. De Berardinis, R.J.; Chandel, N.S. Fundamentals of cancer metabolism. Sci. Adv. 2016, 2, e1600200. [Google Scholar] [CrossRef] [Green Version]
  100. Cully, M. Chemical inhibitors make their RNA epigenetic mark. Nat. Rev. Drug Discov. 2019, 18, 892–894. [Google Scholar] [CrossRef]
  101. Lin, S.; Choe, J.; Du, P.; Triboulet, R.; Gregory, R.I. The m6A Methyltransferase METTL3 Promotes Translation in Human Cancer Cells. Mol. Cell 2016, 62, 335–345. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  102. Narayanaswamy, R.; Levy, M.; Tsechansky, M.; Stovall, G.M.; O’Connell, J.D.; Mirrielees, J.; Ellington, A.D.; Marcotte, E.M. Widespread reorganization of metabolic enzymes into reversible assemblies upon nutrient starvation. Proc. Natl. Acad. Sci. USA 2009, 106, 10147–10152. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  103. van Leeuwen, W.; Rabouille, C. Cellular stress leads to the formation of membraneless stress assemblies in eukaryotic cells. Traffic 2019, 20, 623–638. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  104. Molina, D.M.; Jafari, R.; Ignatushchenko, M.; Seki, T.; Larsson, E.A.; Dan, C.; Sreekumar, L.; Cao, Y.; Nordlund, P. Monitoring drug target engagement in cells and tissues using the cellular thermal shift assay. Science 2013, 341, 84–87. [Google Scholar] [CrossRef]
  105. Lomenick, B.; Hao, R.; Jonai, N.; Chin, R.M.; Aghajan, M.; Warburton, S.; Wang, J.; Wu, R.P.; Gomez, F.; Loo, J.A.; et al. Target identification using drug affinity responsive target stability (DARTS). Proc. Natl. Acad. Sci. USA 2009, 106, 21984–21989. [Google Scholar] [CrossRef] [Green Version]
  106. Boccaletto, P.; MacHnicka, M.A.; Purta, E.; Pitkowski, P.; Baginski, B.; Wirecki, T.K.; De Crécy-Lagard, V.; Ross, R.; Limbach, P.A.; Kotter, A.; et al. MODOMICS: A database of RNA modification pathways. 2017 update. Nucleic Acids Res. 2018, 46, D303–D307. [Google Scholar] [CrossRef]
Figure 1. N6-methyladenosine (m6A) methylation process and its biological functions. (A) m6A writers (methyltransferase) methylate RNA in the adenine nucleobase of amino group at N6 position. The consensus motif of methyltransferase-like 3 (METTL3) is RRA*CH (R = A/G; A* = methylated A; H = A/C/U). Once m6A is deposited on RNA, m6A reader proteins are recruited and determine RNA fates, such as splicing, stability, and translation efficiency, which ultimately affect gene expression. m6A is removed from RNA through demethylation by eraser proteins. (B) METTL16 methylates stem-loop structure in 3’ untranslated region (UTR) of S-adenosyl methionine (SAM) synthase, methionine adenosyltransferase 2A (MAT2A). In SAM-repleted conditions, MAT2A is methylated and degraded. Oppositely, in SAM-depleted conditions, METTL16 induces splicing and expression of MAT2A. (C) Methylation of A4220 in 28S ribosomal RNA (rRNA) by zinc finger CCHC domain-containing protein 4 (ZCCHC4) promotes ribosome assembly and translation. (D) Domain composition of m6A enzymes. (Top, writers) m6A writers contain methyltransferase (MTase) domains. METTL3 contains Cys-Cys-Cys-His (CCCH) zinc finger motifs. METTL16 has two vertebrate conserved region (VCR) domains in C-terminus. ZCCHC4 possesses several zinc finger motifs, including Gly-Arg-Phe (GRF), Cys2-His2 (C2H2), and Cys-Cys-His-Cys (CCHC) domains. (Bottom, erasers) Fat mass and obesity-associated protein (FTO) and alkb homolog 5 (ALKBH5) contain αKG-Fe(II)-dependent dioxygenase domains conserved in dioxygenase family enzymes. WTAP, Wilms’ tumor 1-associated protein; eIF3, eukaryotic initiation factor 3; YTHDF, YTH domain family; YTHDC, YTH domain-containing protein; IGF2BP, insulin-like growth factor 2 mRNA-binding protein; HNRNP, heterogeneous nuclear ribonucleoproteins; FTO-CTD, FTO C-terminal domain.
Figure 1. N6-methyladenosine (m6A) methylation process and its biological functions. (A) m6A writers (methyltransferase) methylate RNA in the adenine nucleobase of amino group at N6 position. The consensus motif of methyltransferase-like 3 (METTL3) is RRA*CH (R = A/G; A* = methylated A; H = A/C/U). Once m6A is deposited on RNA, m6A reader proteins are recruited and determine RNA fates, such as splicing, stability, and translation efficiency, which ultimately affect gene expression. m6A is removed from RNA through demethylation by eraser proteins. (B) METTL16 methylates stem-loop structure in 3’ untranslated region (UTR) of S-adenosyl methionine (SAM) synthase, methionine adenosyltransferase 2A (MAT2A). In SAM-repleted conditions, MAT2A is methylated and degraded. Oppositely, in SAM-depleted conditions, METTL16 induces splicing and expression of MAT2A. (C) Methylation of A4220 in 28S ribosomal RNA (rRNA) by zinc finger CCHC domain-containing protein 4 (ZCCHC4) promotes ribosome assembly and translation. (D) Domain composition of m6A enzymes. (Top, writers) m6A writers contain methyltransferase (MTase) domains. METTL3 contains Cys-Cys-Cys-His (CCCH) zinc finger motifs. METTL16 has two vertebrate conserved region (VCR) domains in C-terminus. ZCCHC4 possesses several zinc finger motifs, including Gly-Arg-Phe (GRF), Cys2-His2 (C2H2), and Cys-Cys-His-Cys (CCHC) domains. (Bottom, erasers) Fat mass and obesity-associated protein (FTO) and alkb homolog 5 (ALKBH5) contain αKG-Fe(II)-dependent dioxygenase domains conserved in dioxygenase family enzymes. WTAP, Wilms’ tumor 1-associated protein; eIF3, eukaryotic initiation factor 3; YTHDF, YTH domain family; YTHDC, YTH domain-containing protein; IGF2BP, insulin-like growth factor 2 mRNA-binding protein; HNRNP, heterogeneous nuclear ribonucleoproteins; FTO-CTD, FTO C-terminal domain.
Metabolites 11 00080 g001
Figure 2. Potential interplay of m6A methylation with cellular metabolic pathways. (A) List of metabolites affecting activities of m6A writers and erasers. Grey, activators; white, inhibitors. (B) Schematic of metabolic pathways that can influence m6A methylation and demethylation processes. One-carbon metabolism produces SAM, a methyl donor of m6A modification. S-adenosyl homocysteine (SAH), the by-product of methylation, inhibits writer activity. On the other hand, the oxidative demethylation of m6A by erasers needs α-ketoglutarate (αKG), oxygen (O2), and iron [Fe(II)] as cofactors. Tricarboxylic acid (TCA) cycle produces co-factors that activate (αKG) or inhibit (fumarate and succinate) demethylase activity. Iron is delivered to cells as transferrin–iron complex, wherein low lysosomal pH causes release of free iron ions into the cytoplasm. Pentose phosphate pathway converts nicotinamide adenine dinucleotide phosphate (NADP+) to NADPH, another cofactor for demethylases. R-2HG, R-2-hydroxyglutrate; Met, methionine; THF, tetrahydrofolate; Hcy, homocysteine.
Figure 2. Potential interplay of m6A methylation with cellular metabolic pathways. (A) List of metabolites affecting activities of m6A writers and erasers. Grey, activators; white, inhibitors. (B) Schematic of metabolic pathways that can influence m6A methylation and demethylation processes. One-carbon metabolism produces SAM, a methyl donor of m6A modification. S-adenosyl homocysteine (SAH), the by-product of methylation, inhibits writer activity. On the other hand, the oxidative demethylation of m6A by erasers needs α-ketoglutarate (αKG), oxygen (O2), and iron [Fe(II)] as cofactors. Tricarboxylic acid (TCA) cycle produces co-factors that activate (αKG) or inhibit (fumarate and succinate) demethylase activity. Iron is delivered to cells as transferrin–iron complex, wherein low lysosomal pH causes release of free iron ions into the cytoplasm. Pentose phosphate pathway converts nicotinamide adenine dinucleotide phosphate (NADP+) to NADPH, another cofactor for demethylases. R-2HG, R-2-hydroxyglutrate; Met, methionine; THF, tetrahydrofolate; Hcy, homocysteine.
Metabolites 11 00080 g002
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Kim, J.; Lee, G. Metabolic Control of m6A RNA Modification. Metabolites 2021, 11, 80. https://doi.org/10.3390/metabo11020080

AMA Style

Kim J, Lee G. Metabolic Control of m6A RNA Modification. Metabolites. 2021; 11(2):80. https://doi.org/10.3390/metabo11020080

Chicago/Turabian Style

Kim, Joohwan, and Gina Lee. 2021. "Metabolic Control of m6A RNA Modification" Metabolites 11, no. 2: 80. https://doi.org/10.3390/metabo11020080

APA Style

Kim, J., & Lee, G. (2021). Metabolic Control of m6A RNA Modification. Metabolites, 11(2), 80. https://doi.org/10.3390/metabo11020080

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop